Informatica ETL Developer

Skills

Bachelor's degree in Computer Science Information Technology or a related field (or equivalent work experience) Strong experience with Informatica PowerCenter or other ETL tools Proficiency in SQL for data querying and manipulation Knowledge of data warehousing concepts and data modeling Familiarity with databases (e.g. Oracle SQL Server) and various data formats (e.g. CSV XML JSON) Problem-solving and troubleshooting skills Attention to detail and commitment to data quality Excellent communication and collaboration skills Ability to work independently and as part of a team Experience with performance tuning and optimization of ETL processes is a plus

Description

Informatica for ETL and SQL
Needs experience with commission flow and ICM systems experience as well as Informatica experience and is a major bonus if they have reporting experience, as this may come into play later in the assignment.
Cultural Fit:

Agile mindset
Very high sense of ownership, as it is key that all team members continuously work towards progress, rather than wait for work to be assigned. Need to be strong communicators.
Good problem solvers and must have an end-to-end way of thinking. Bring ideas of "how could we do this" to the table/thought leadership. This is a new product for them, not BAU and will be plenty of opportunity to enhance

Responsibilities

• Requirements Analysis: Collaborate with business analysts and stakeholders to understand data integration requirements and translate them into technical specifications
• ETL Development: Design, develop, and maintain ETL processes using Informatica PowerCenter or similar tools to extract data from source systems, transform it according to business rules, and load it into target systems
• Data Extraction: Extract data from diverse source systems, which may include databases, flat files, APIs, and other data sources
• Data Transformation: Implement data transformations, cleansing, and enrichment processes to ensure data quality and alignment with business needs
• Data Loading: Load transformed data into data warehouses, data marts, or other target systems, ensuring data consistency and accuracy
• Performance Optimization: Optimize ETL processes for performance, scalability, and efficiency. Identify and resolve performance bottlenecks
• Error Handling and Logging: Develop robust error handling mechanisms to capture, log, and manage ETL errors. monitor, and troubleshoot data integration issues
• Data Quality and Validation: Implement data quality checks and validation routines to maintain data integrity and compliance with business rules and regulations
• Documentation: Maintain detailed documentation of ETL processes, mappings, transformations, and configurations. Ensure documentation is up to date and accessible to team members
• Testing and Quality Assurance: Create and execute test cases to validate ETL processes, ensuring data accuracy, completeness, and reliability
• Deployment: Deploy ETL jobs to production environments and schedule them for regular execution. Coordinate with system administrators and other teams for deployment
• Collaboration: Collaborate with data architects, database administrators, business analysts, and other stakeholders to understand data requirements and ensure seamless data integration
• Security and Compliance: Ensure data integration processes adhere to security policies, data privacy regulations, and compliance standards
• Version Control: Use version control systems to manage ETL code and configurations